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Transiting exoplanets orbiting active stars frequently occult starspots on the visible stellar disc. We must correct transit observations from these contaminations, but can we also get some information out of them? We tested the capabilities of JWST’s NIRSpec/Prism and the proposed NIRCam/F150W2+F322W2 modes to determine occulted starspot temperatures., {"references":["Batalha et al., 2017, PASP, 129, 064501","Schlawin et al., 2016, PASP, 129, 015001","Montalto et al., 2014, MNRAS, 444, 1721","Sarkar et al., 2020, MNRAS, 491, 378"]}

Supplemental Material for Development and evaluation of probabilistic forecasting methods for small area populations by Irina Grossman, Kasun Bandara, Tom Wilson, and Michael Kirley in Environment and Planning B: Urban Analytics and City Science

The Vera C. Rubin Observatory's LSST will be so crowded, even outside the Galactic plane, that standard cross-matching algorithms with other surveys will fail. In this poster I describe the effect of blending from contaminant sources on the astrometry and photometry of LSST and other catalogues (with WISE as a stand-in example for LSST crowding at its full 10-year depth), using Gaia and its extremely high precision data to reveal this hidden problem which causes up to 50% of Gaia-WISE matches to be missed, detailing how to overcome this problem with a Bayesian cross-match framework. I introduce the generic "Astrometric Uncertainty Function", discuss the use of the photometric information to break false match degeneracies, and briefly touch on additional benefits this new cross-match method has, such as the natural inclusion of proper motion when cross-matching datasets with no proper motion information and statistics on the level of flux contamination sources in each catalogue suffers., {"references":["Wilson & Naylor (2017, MNRAS, 468, 2517)","Wilson & Naylor (2018, MNRAS, 473, 5570)","Wilson & Naylor (2018, MNRAS, 481, 2148)","Wilson (2022, RNAAS, 6, 60)","Wilson (2022, RASTI, accepted)","Sutherland & Saunders (1992, MNRAS, 259, 413)","Wright et al. (2010, AJ, 140, 1868)"]}

Small area population forecasts are widely used by government and business for a variety of planning, research and policy purposes, and often influence major investment decisions. Yet, the toolbox of small area population forecasting methods and techniques is modest relative to that for national and large subnational regional forecasting. In this paper, we assess the current state of small area population forecasting, and suggest areas for further research. The paper provides a review of the literature on small area population forecasting methods published over the period 2001–2020. The key themes covered by the review are extrapolative and comparative methods, simplified cohort-component methods, model averaging and combining, incorporating socioeconomic variables and spatial relationships, ‘downscaling’ and disaggregation approaches, linking population with housing, estimating and projecting small area component input data, microsimulation, machine learning, and forecast uncertainty. Several avenues for further research are then suggested, including more work on model averaging and combining, developing new forecasting methods for situations which current models cannot handle, quantifying uncertainty, exploring methodologies such as machine learning and spatial statistics, creating user-friendly tools for practitioners, and understanding more about how forecasts are used. Supplementary Information The online version contains supplementary material available at 10.1007/s11113-021-09671-6.

In this talk I will discuss the effect of blending from hidden, contaminant sources on the astrometry and photometry of catalogues such as LSST and WISE, using Gaia and its extremely high precision data to reveal this hidden problem which causes up to 50% of Gaia-WISE matches to be missed, and discuss how to overcome this problem with a Bayesian cross-match framework. I will introduce the generic "Astrometric Uncertainty Function", discuss the use of the photometric information to break false match degeneracies, and briefly touch on additional benefits this new cross-match method has, such as the natural inclusion of proper motion when cross-matching datasets with no proper motion information and statistics on the level of flux contamination sources in each catalogue suffers.

Full list of authors: Price-Whelan, Adrian M.; Lim, Pey Lian; Earl, Nicholas; Starkman, Nathaniel; Bradley, Larry; Shupe, David L.; Patil, Aarya A.; Corrales, Lia; Brasseur, C. E.; Noethe, Maximilian; Donath, Axel; Tollerud, Erik; Morris, Brett M.; Ginsburg, Adam; Vaher, Eero; Weaver, Benjamin A.; Tocknell, James; Jamieson, William; van Kerkwijk, Marten H.; Robitaille, Thomas P.; Merry, Bruce; Bachetti, Matteo; Gunther, H. Moritz; Aldcroft, Thomas L.; Alvarado-Montes, Jaime A.; Archibald, Anne M.; Bodi, Attila; Bapat, Shreyas; Barentsen, Geert; Bazan, Juanjo; Biswas, Manish; Boquien, Mederic; Burke, D. J.; Cara, Daria; Cara, Mihai; Conroy, Kyle E.; Conseil, Simon; Craig, Matthew W.; Cross, Robert M.; Cruz, Kelle L.; D'Eugenio, Francesco; Dencheva, Nadia; Devillepoix, Hadrien A. R.; Dietrich, Jorg P.; Eigenbrot, Arthur Davis; Erben, Thomas; Ferreira, Leonardo; Foreman-Mackey, Daniel; Fox, Ryan; Freij, Nabil; Garg, Suyog; Geda, Robel; Glattly, Lauren; Gondhalekar, Yash; Gordon, Karl D.; Grant, David; Greenfield, Perry; Groener, Austen M.; Guest, Steve; Gurovich, Sebastian; Handberg, Rasmus; Hart, Akeem; Hatfield-Dodds, Zac; Homeier, Derek; Hosseinzadeh, Griffin; Jenness, Tim; Jones, Craig K.; Joseph, Prajwel; Kalmbach, J. Bryce; Karamehmetoglu, Emir; Kaluszynski, Mikolaj; Kelley, Michael S. P.; Kern, Nicholas; Kerzendorf, Wolfgang E.; Koch, Eric W.; Kulumani, Shankar; Lee, Antony; Ly, Chun; Ma, Zhiyuan; MacBride, Conor; Maljaars, Jakob M.; Muna, Demitri; Murphy, N. A.; Norman, Henrik; O'Steen, Richard; Oman, Kyle A.; Pacifici, Camilla; Pascual, Sergio; Pascual-Granado, J.; Patil, Rohit R.; Perren, Gabriel, I; Pickering, Timothy E.; Rastogi, Tanuj; Roulston, Benjamin R.; Ryan, Daniel F.; Rykoff, Eli S.; Sabater, Jose; Sakurikar, Parikshit; Salgado, Jesus; Sanghi, Aniket; Saunders, Nicholas; Savchenko, Volodymyr; Schwardt, Ludwig; Seifert-Eckert, Michael; Shih, Albert Y.; Jain, Anany Shrey; Shukla, Gyanendra; Sick, Jonathan; Simpson, Chris; Singanamalla, Sudheesh; Singer, Leo P.; Singhal, Jaladh; Sinha, Manodeep; Sipocz, Brigitta M.; Spitler, Lee R.; Stansby, David; Streicher, Ole; Sumak, Jani; Swinbank, John D.; Taranu, Dan S.; Tewary, Nikita; Tremblay, Grant R.; De Val-Borro, Miguel; Vasovic, Zlatan; Van Kooten, Samuel J.; Verma, Shresth; Cardoso, Jose Vinicius de Miranda; Williams, Peter K. G.; Wilson, Tom J.; Winkel, Benjamin; Wood-Vasey, W. M.; Xue, Rui; Yoachim, Peter; Zhang, Chen; Zonca, Andrea; Astropy Project Contributors; TARDIS Collaboration; Astropy Coordination Comm.--This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates on the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project. © 2022. The Author(s). Published by the American Astronomical Society., We acknowledge the Gordon and Betty Moore Foundation for their continued financial support. This work is partially supported by NASA under grant No. 80NSSC22K0347 issued through the NASA ROSES program. This work is partially supported by the international Gemini Observatory, a program of NSF’s NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation, on behalf of the Gemini partnership of Argentina, Brazil, Canada, Chile, the Republic of Korea, and the United States of America. We also thank NumFOCUS and the Python Software Foundation for financial support. J.A.A.-M. acknowledges funding support from Macquarie University through the International Macquarie University Research Excellence Scholarship (“iMQRES”). A.B. was supported by the Lendület Program of the Hungarian Academy of Sciences, project No. LP2018-7, and the KKP-137523 “SeismoLab” Élvonal grant of the Hungarian Research, Development and Innovation Office (NKFIH). M.B. gratefully acknowledges support from the ANID BASAL project FB210003 and the FONDECYT regular grant 1211000. F.D.E. acknowledges funding through the H2020 ERC Consolidator grant 683184, the ERC Advanced grant 695671 “QUENCH” and support from the Science and Technology Facilities Council (STFC). S.G. made contributions to Astropy as part of the Google Summer of Code 2021. S.G. acknowledges some intellectual support from the CCAD-UNC-NOVA. Funding for the Stellar Astrophysics Centre is provided by The Danish National Research Foundation (grant agreement No.: DNRF106). N.K. acknowledges support from the MIT Pappalardo fellowship. K.A.O. acknowledges support from the European Research Council (ERC) through Advanced Investigator grant to C.S. Frenk, DMIDAS (GA 786910). C.P. is supported by the Canadian Space Agency under a contract with NRC Herzberg Astronomy and Astrophysics. S.P. has been supported by Spanish MINECO-FEDER grant RTI2018-096188-B-I00 J.P.G. acknowledges funding support from Spanish public funds for research from project PID2019-107061GB-C63 from the “Programas Estatales de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i y de I+D+i Orientada a los Retos de la Sociedad,” as well as from the State Agency for Research of the Spanish MCIU through the “Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). N.S. acknowledges support from the National Science Foundation through the Graduate Research Fellowship Program under grant 1842402. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Supported by the international Gemini Observatory, a program of NSF’s NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation, on behalf of the Gemini Observatory partnership: the National Science Foundation (United States), National Research Council (Canada), Agencia Nacional de Investigación y Desarrollo (Chile), Ministerio de Ciencia, Tecnología e Innovación (Argentina), Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). Parts of this research were supported by the Australian Research Council Centre of Excellence for All-Sky Astro-physics in 3 Dimensions (ASTRO 3D), through project number CE170100013. D.S. is supported by STFC grant ST/S000240/1. N.S. acknowledges the support of the Science and Engineering Research Council of Canada (NSERC) Canadian Graduate Scholarship—Doctoral Program, [funding reference numbers CGSD547212020].

This poster presents a radiative transfer study of T Tauri stars. We compare synthetic and observed hydrogen emission at multiple wavelengths., {"references":["Harries, T. J., Haworth, T. J., Acreman, D., Ali, A. & Douglas, T. The TORUS radiation transfer code. Astronomy and Computing 27, 63–95 (2019)","Reipurth, B., Pedrosa, A. & Lago, M. T. V. T. Hα emission in pre-main sequence stars. I. an atlas of line profiles. Astronomy and Astrophysics Supplement 120, 229–256 (1996)."]}

A comparison of synthetic and observed hydrogen emission lines from T Tauri stars.

Traditional photometric catalogue matching will fail for Rubin Obs. LSST, as typical 2” error circles will contain up to 10 random objects. Bayesian cross-matching techniques which include the astrometric uncertainty of the observations ultimately assume that the Astrometric Uncertainty Function of the sources is Gaussian, which will not apply to LSST. The extreme source densities and significant number of objects with no known proper motion mean that systematic effects, not noise-based scatter, dominant the separations of objects between LSST and other surveys. As part of the LSST:UK consortium we have developed and are implementing methods to handle these effects, vital to being able to trust any composite dataset created, and will be producing robust cross-matches between LSST and a wide range of other catalogues., {"references":["Sutherland & Saunders (1992): On the likelihood ratio for source identification.","Wright et al. (2010): The Wide-field Infrared Survey Explorer (WISE): Mission Description and Initial On-orbit Performance","Ricker et al. (2015): Transiting Exoplanet Survey Satellite (TESS)","Wilson & Naylor (2017): The effect of unresolved contaminant stars on the cross-matching of photometric catalogues","Wilson & Naylor (2018): Improving catalogue matching by supplementing astrometry with additional photometric information","Wilson & Naylor (2018): A contaminant-free catalogue of Gaia DR2-WISE Galactic plane matches: including the effects of crowding in the cross-matching of photometric catalogues"]}

Auckland is the largest city in New Zealand with 1.6 million residents. This major metropolitan region is situated upon the Auckland Volcanic Field (AVF), posing a considerable risk to the city’s population and essential services. On 17 December 2018, a workshop jointly run by DEVORA (Determining Volcanic Risk in Auckland) and Auckland Emergency Management (AEM) was held to discuss evacuation decision-support options in the event of a volcanic crisis in Auckland. The workshop brought together emergency management officials, members of the emergency services, transportation managers, academics and researchers. Participants discussed existing decision-making processes and communication pathways before being presented with how ongoing research could support decision-makers with volcanic crisis planning and management. An exercise was conducted to learn the types of decisions and related information requirements of different groups at different stages of a crisis. The exercise focused on three early stages of an existing AVF eruption crisis scenario centred on Birkenhead: Initial unrest; heightened unrest; and initial eruption phase. Each stage of the scenario was presented to groups along with a series of questions relating to their likely actions based on the information presented. The purpose of the exercise was to learn what type of information would be required at each step, and to identify how ongoing research into a quantitative decision-support framework using cost-benefit analysis could support decision-makers in a future AVF eruption. The exercise revealed that risk to life is a primary consideration for making an evacuation decision; the declaration of a state of emergency is critical before making an evacuation call; key locations and services critical for crisis management exist and can be identified in advance of a crisis; and a staged evacuation would likely be recommended. The findings from this workshop will support ongoing research exploring how hazard and risk information can best be presented to support decision-makers in the event of an evacuation during an AVF event. (auth)

Tom Wilson is Postdoctoral Research Fellow and Martin Bell is Associate Professor and Director both are with the Queensland Centre for Population Research, School of Geography, Planning and Architecture, The University of Queensland; Glen Heyen is Senior Statistician in the Office of Economic and Statistical Research, Queensland Government and Alison Taylor is Principal Demographer in the Planning Information and Forecasting Unit, Department of Local Government and Planning, Queensland Government. The Queensland Government recently released its 2001-based population projections for the State and its statistical divisions. This paper reports on the main features of the projections to 2051 at the State level and to 2026 at the statistical division scale, the various projection assumptions made, and the new multiregional projection model written specifically for this round of projections. The projections indicate that Queensland is likely to experience very substantial population growth in coming decades, increasing concentration in the south east, and significant population ageing. Pagination on item is incorrect Copyright. Monash University and the author/s

This paper examines how the Northern Territory’s Indigenous demography has changed over recent decades, an assessment made possible by a recently constructed Indigenous demographic database covering the period 1966–2001. The paper then presents population forecasts to 2031 prepared with a new population projection program specially designed to model the population by indigenous status. The results show that considerable growth and modest ageing of the NT Indigenous population may be expected. Copyright. Monash University and the author/s

The number of seats in the Australian House of Representatives allocated to each state and territory is determined largely by population size, with periodic recalculations made to allow for the changing geographical distribution of the nation’s population. This paper describes how the calculations are made and presents the results of the Australian Electoral Commissioner’s November 2005 seat determination. It focuses mostly on the case of the Northern Territory (NT). In the 2000 determination, for the first time, the NT was allocated a second seat, which would have been lost in the 2003 determination had there not been an inquiry and subsequent legislation changes. In the most recent determination the second seat was retained by a small margin. The paper explains the calculations which decided this matter and goes on to discuss the prospects for future representation of the Territory Copyright. Monash University and the author/s

La utilización de las tecnologías de la información en la planificación y diseño de sistemas de información sobrepasa, actualmente, el alcance de un simple problema técnico o tecnológico. Encontramos una gran separación entre las necesidades globales de la organización y la perspectiva de los distintos usuarios del sistema de información. Es claro que tanto las necesidades de cada uno de ellos, tanto en su relación a su situación en la organización como ante los diferentes estilos de aprendizaje, constituyen factores que inciden muy directamente ante sistemas cuya interfaz actúa y responde de forma plana, sea cual fuere el tipo de usuario. Este trabajo presenta una visión en la línea del usuario individual en orden a un desarrollo más propicio de los sistemas de información, más cercanos a los usuarios. ABSTRACT: Actually, the useof information technologies into the process of planning and design information systems exceeds the level of an elemental technical or technological application problem. We can find a great separation between the global needs of an organization and the information systems users' view. These sets of needs, related with their position into the organization and their different learning styles, clearly, are factors that affect more directly to systems, specially those their interface would be indepent of the users. This work shows a innovative view in order to implement information systems more nearby to the end user

Additional file 1. Figure S1: Sexual identity questions in HILDA and the GSS. Table S1: Relative standard errors for sexual identity percentages in Table 1. Table S2: Relative standard errors for the sexual minority percentages in Table 2.

Additional file 1. Figure S1: Sexual identity questions in HILDA and the GSS. Table S1: Relative standard errors for sexual identity percentages in Table 1. Table S2: Relative standard errors for the sexual minority percentages in Table 2.